The subject matter discussed in this section should not be assumed to be prior art merely as a result of its mention in this section. Similarly, a problem mentioned in this section or associated with the subject matter provided as background should not be assumed to have been previously recognized in the prior art. The subject matter in this section merely represents different approaches, which in and of themselves can also correspond to implementations of the claimed technology.
A vast amount of data, more than ever before, is available to organizations from multitude of sources. This presents an unprecedented opportunity to organizations to learn more about their businesses, markets and customers. The databases to answer these analytic queries are built from transaction processing systems. The computing hardware to build and query these analytic databases is very efficient in handling a variety of end user analytical queries and build requests. However, the end users have no control on such computing hardware after database build tasks and queries are dispatched for processing. The computing hardware processes end. user analytic queries and database build requests based on available resources without giving any consideration to ordering amongst these requests.
An opportunity arises to enable users to efficiently process their analytic queries and database build requests in an ordered manner without impacting the operation and performance of the computing hardware. Improved user experience, higher response times, reduced errors, and greater computational efficiency may result.